Objective To identify factors affecting and key environmental factors of the Oncomelania hupensis snail density in the Yangtze River Delta region using machine learning methods. Methods Administrative village-level O. hupensis snail survey data in the Yangtze River Delta (including Shanghai Municipality, Jiangsu Province, Zhejiang Province and Anhui Province) from 2011 to 2021 were retrieved from the Information Management System for Parasitic Disease Control of Chinese Center for Disease Control and Prevention. Environmental factor data were captured from the Google Earth Engine platform, including elevation, slope, terrain, normalized difference vegetation index (NDVI), vegetation type, soil type, total petroleum hydrocarbon (TPH), ammonium nitrogen, inorganic nitrogen, dissolved oxygen, pH of water, chemical oxygen demand (COD) and inorganic phosphorus, and climatic factor data in the study region were retrieved from the Copernicus Climate Data Store, including annual precipitation, aridity index and annual mean temperature (AMT). O. hupensis snail survey data in the Yangtze River Delta region from 2011 to 2021 were randomly divided into a training set (70%) and a test set (30%), and five machine learning models were selected for machine learning model construction and comparative analysis of the O. hupensis snail density using the software R 4.3.0, including random forest (RF), eXtreme gradient boosting (XGBoost), support vector machine (SVM), gradient boosting machine (GBM) and neural network (NN). The XGBoost model was employed to construct a predictive model for the O. hupensis snail density, and the impact of each environmental factor on O. hupensis snail distribution was quantified. The SHapley Additive exPlanations (SHAPs) values were calculated to estimate the average contribution of each variable to the model prediction, and the core environmental factors affecting the O. hupensis snail population density were screened. Results Among the five machine learning models, the XGBoost model exhibited the optimal comprehensive performance, with the coefficient of determination (R²) of 0.855, mean squared error (MSE) of 0.188, root mean squared error (RMSE) of 0.434 and mean absolute error (MAE) of 0.155, respectively. Analysis of factors affecting the O. hupensis snail density with the XGBoost model showed that among the 16 environmental factors, the top four high-impact factors ranked by SHAPs values included annual precipitation, elevation, aridity index and NDVI, with cumulative SHAPs contributions of 75%, which was higher than that of other environmental factors. If NDVI was higher than 0.6, the O. hupensis snail density increased with NDVI and peaked if NDVI was 0.8 (1.60 snails/0.1 m²). The O. hupensis snail density increased with elevation if the elevation ranged from 14 to 40 m, and slowly rose if the annual precipitation ranged from 900 to 1 300 mm, and then increased rapidly to the peak (1.52 snails/0.1 m²) if the annual precipitation ranged from 1 300 to 1 500 mm. In addition, the O. hupensis snail density increased rapidly to the maximum (1.60 snails/0.1 m²) if the aridity index ranged from 0.8 to 1.1, and decreased gradually if the aridity index exceeded 1.1. Conclusions The XGBoost model shows excellent performance in prediction of the O. hupensis snail density and identification of key environmental factors in the Yangtze River Delta region. Annual precipitation, elevation, aridity index and NDVI are key environmental factors affecting the distribution and density of O. hupensis snails in the Yangtze River Delta region.

Background Sunshine duration is closely associated with population mental health and emotional states, although its relationship with mental and behavioral disorders (MBD) remains insufficiently studied. Objective To analyze the effect of sunshine duration on hospital admissions for MBD in Zigong City, Sichuan Province. Methods Hospital admission records for MBD from 10 medical institutions, meteorological data, and ambient air pollutant concentrations were collected in Zigong City from January 1, 2019 to December 31, 2024. A distributed lag non-linear model (DLNM) was employed to calculate single-day and cumulative lag effects of different sunshine duration exposures—0 h (P₀, P₅, P₂₅), 6 h (P₇₅), and 10.4 h (P₉₅)—on hospitalization risks for MBD, stratified by diagnostic category, sex, and age groups. Results This study analyzed 36597 hospital admissions for MBD in Zigong City. The exposure-response curve for sunshine duration at lag 0 d exhibited an inverted N-shaped pattern, with minimum relative risk (RR) of hospitalizations observed at 14 h sunshine duration. The immediate effects of different levels of sunshine duration on the hospitalization risk for MBD, schizophrenia, schizotypal and delusional disorders (SSDD), and neurotic, stress-related and somatoform disorders (NSSD) were significant, with the cumulative effect peaking at lags 12–13 days. For extremely short sunshine duration 0 h, the maximum relative risk (RR) values (with 95% confidence intervals, 95%CI) of hospitalization risk were 1.209 (1.001, 1.459) at lag 1 d for SSDD patients and 1.398 (1.133, 1.724) at lag 0 d for NSSD patients, respectively. The cumulative effect on hospitalization risk induced by short sunshine duration 6 h was higher than that induced by extremely short sunshine duration 0 h and long sunshine duration 10.4 h. Among populations stratified by gender and age, male patients and those aged over 70 years had higher hospitalization risks. For short sunshine duration 6 h, the cumulative RR (CRR) value (95%CI) of hospitalization risk for male MBD patients was 3.373 (1.362, 8.358) at cumulative lag 0–12 d, which was higher than that for female patients [2.943 (1.471, 5.889) at cumulative lag 0–13 d]. The population aged over 70 years was more sensitive to single-day and cumulative lag effects on hospitalization risk than other age groups. For short sunshine duration 6 h, the RR and CRR values (95%CI) of single-day and cumulative lag effects on hospitalization risk were 1.336 (1.002, 1.783) at lag 0 day and 5.085 (1.680, 15.392) at cumulative lag 0–12 d, respectively. At lag 13 d, long sunshine duration 10.4 h exposure was associated with depression hospitalizations in patients <20 years with RR=1.127 (95%CI: 1.002, 1.270). Conclusion When the daily sunshine duration is less than 14 h, it will increase the hospitalization risk of MBD in the population to varying degrees, with both single-day and cumulative lag effects. It is recommended that the public, especially vulnerable groups such as people with MBD aged 70 years and above and those with depression under 20 years, strengthen health protection to reduce the health risks caused by changes in sunshine.

Traditional Chinese medicine （TCM） clinical trials face challenges such as low participant compliance， insufficient geographical coverage， and cost-effectiveness imbalances. Decentralized clinical trials （DCT）， enabled by digital technology for remote data collection and monitoring， offer a new direction for TCM clinical trial research. This article systematically reviews three novel clinical trial design models. Combining the holistic concept and indivi-dualized treatment characteristics of TCM， it analyzes the challenges currently faced in TCM DCT practice， including the digitization and standardization of TCM theory， data security， privacy protection and patient engagement difficu-lties， insufficient ethical review and regulatory system adaptation， inadequate personnel training， and a shortage of interdisciplinary talent. Addressing these challenges， the article proposes methodological recommendations for DCT implementation that align with the principles of TCM diagnosis and treatment. These recommendations include promoting the intelligentization and standardization of TCM practices， constructing a full-chain data security and privacy protection system， improving the ethical framework and clarifying regulatory responsibilities， and cultivating and building interdisciplinary talent and capabilities， which provide theoretical and technical references for establishing standardized DCT practices in TCM.

Traditional Chinese medicine （TCM） clinical trials face challenges such as low participant compliance， insufficient geographical coverage， and cost-effectiveness imbalances. Decentralized clinical trials （DCT）， enabled by digital technology for remote data collection and monitoring， offer a new direction for TCM clinical trial research. This article systematically reviews three novel clinical trial design models. Combining the holistic concept and indivi-dualized treatment characteristics of TCM， it analyzes the challenges currently faced in TCM DCT practice， including the digitization and standardization of TCM theory， data security， privacy protection and patient engagement difficu-lties， insufficient ethical review and regulatory system adaptation， inadequate personnel training， and a shortage of interdisciplinary talent. Addressing these challenges， the article proposes methodological recommendations for DCT implementation that align with the principles of TCM diagnosis and treatment. These recommendations include promoting the intelligentization and standardization of TCM practices， constructing a full-chain data security and privacy protection system， improving the ethical framework and clarifying regulatory responsibilities， and cultivating and building interdisciplinary talent and capabilities， which provide theoretical and technical references for establishing standardized DCT practices in TCM.

Implementation science (IS) aims to systematically analyze and address the real-world gaps from evidence to practice and the influencing factors of the context. It is necessary to carry out qualitative research to gather relevant implementation outcomes. Nevertheless, traditional qualitative analysis has issues such as consuming a great deal of time and energy, and it is unable to promptly provide the crucial data required for implementation science research. The Rapid Qualitative Analysis (RQA) method, through semi-structured interviews and the adoption of techniques such as immediate data condensation and matrix analysis, can effectively shorten the cycle of qualitative data collection and data processing. RQA can promptly identify social determinants of health such as structural barriers, facilitators, and the behavioral characteristics of target groups. It provides a real-time basis for public health decision-making, the interpretation of complex social phenomena, and the process and effectiveness evaluation of research projects. Although RQA is difficult to conduct in-depth theoretical analysis based on grounded theory, its efficiency and flexibility make it the preferred tool for large-scale and time-sensitive research. Thus, it has been widely applied in implementation science research. This paper sorts out the core concepts and commonly used technical methods of RQA, as well as the differences between RQA and traditional qualitative analysis. It also explores the applications of RQA in intervention optimization, process evaluation, and implementation outcome evaluation. By integrating specific cases, this paper clarifies its application value in the field of implementation science. In the future, it is advisable to explore the integration of RQA with technologies such as artificial intelligence and big data, in order to bridge the gap between the transformation of scientific research achievements into practice. Under circumstances of limited resources or tight time constraints, RQA can be used to efficiently conduct implementation science research, providing convenient and scientific methodological and technical support for accelerating evidence-based practice.

To understand the progress of, summarize the lessons learned from and analyze the challenges in the national schistosomiasis elimination program of China in 2024, this article presented the endemic situation of schistosomiasis and national schistosomiasis surveillance results in the People’s Republic of China in 2024. By the end of 2024, Shanghai Municipality, Zhejiang Province, Fujian Province, Guangdong Province and Guangxi Zhuang Autonomous Region continued to consolidate schistosomiasis elimination achievements, and 7 provinces of Jiangsu, Sichuan, Yunnan, Hubei, Hunan, Anhui and Jiangxi maintained the criteria of schistosomiasis transmission interruption. A total of 450 counties (cites, districts) were found to be endemic for schistosomiasis in China in 2024, including 26 061 endemic villages covering 73 630 500 residents at risk of infections. Among the 450 counties (cities, districts) endemic for schistosomiasis, 388 (86.22%) achieved the criteria of schistosomiasis elimination and 62 (13.78%) achieved the criteria of transmission interruption. In 2024, a total of 4 102 624 individuals received immunological tests for schistosomiasis in China, with 44 823 sero-positives identified (1.09% seroprevalence), and a total of 169 722 individuals received parasitological examinations, with 1 egg-positives detected. A total of 27 321 cases with advanced schistosomiasis were documented in China by the end of 2024. In 2024, a total of 575 686 bovines were raised in schistosomiasis-endemic villages of China, and 113 842 bovines received immunological tests, with 235 sero-positives detected (0.21% seroprevalence), while no egg-positives were identified among the 167 475 bovines receiving parasitological examinations. In 2024, snail survey was performed covering an area of 680 498.27 hm² in China, and 190 778.66 hm² snail habitats were identified, including 59.09 hm² emerging snail habitats and 704.23 hm² reemerging snail habitats. In 2024, a total of 19 665 schistosomiasis patients receiving chemotherapy with praziquantel in China, and expanded chemotherapy was given to humans at 571 722 person-times and to bovines at 306 740 herd-times. In addition, snail control with chemical treatment covered 117 111.37 hm² snail habitats across China in 2024, and the actual area of chemical treatment was 66 562.95 hm², while environmental improvements were performed in snail habitats covering an area of 1 374.26 hm². The national schistosomiasis surveillance results showed that the mean prevalence rates of Schistosoma japonicum infections were both 0 among humans and bovines in China in 2024, and no S. japonicum infection was detected in snails. These data demonstrated that the prevalence of schistosomiasis remained at a low level in China in 2024; however, the areas of snail habitats remained high and the number of fenced cattle showed a slight increase. To address these risks, it is imperative to maintain the integrated strategy with an emphasis on management of the source of S. japonicum infection and intensified snail control in high-risk areas, and to reinforce schistosomiasis surveillance and forecast and snail control in high-risk areas.

Objective: To investigate the indoor fine particulate matter (PM 2.5 ) pollution and its influencing factors in children s bedrooms using solid fuel, so as to provide evidence for effective strategy to reduce PM 2.5 pollution. Methods: From December 2019 to November 2020, 198 households (108 in the north, 90 in the south) from two pilots in the north(Jiamusi in Heilongjiang Province) and south of China (Mianyang in Sichuan Province) were selected, and status of solid fuels using were obtained through home visits, dynamic changes in PM 2.5 concentrations in children s bedrooms were monitored by using real time online instruments, and the influencing factors of PM 2.5 pollution were analyzed by using a mixed effects model. Results: During the monitoring period, the daily PM 2.5 concentrations in the northern and southern pilot were 78.33 (40.50, 154.80) and 38.54(26.20, 58.46) μg/m 3, respectively, exceeding standard rates of 44.57% and 33.22%. During the heating period, the daily PM 2.5 concentrations in the northern and southern pilot were 212.50(133.60,244.10) and 104.42(73.97, 134.90) μg/m 3, respectively, with over standard rates of 96.75% and 86.96%. The mixed effects model analysis results showed that children s bedroom PM 2.5 concentrations were associated with solid fuel usage duration, window opening time, room layout (shared entrance door between kitchen and bedroom), indoor smoking, indoor humidity, and solid fuel use in the bedroom ( β =0.19, -0.05, 1.20, 0.43, 0.02, 0.35, all P <0.05). Conclusion Solid fuel combustion significantly comtributes to PM 2.5 pollution in children s bedrooms, with more pronounced impacts observed in northern China compared to southern regions.

OBJECTIVE To study the improvement effects and mechanism of proanthocyanidins （PACs） on steroid-induced osteonecrosis of the femoral head （SONFH） in rabbits based on the receptor-interacting protein kinase 1 （RIPK1）/RIPK3/mixed lineage kinase domain-like protein （MLKL） signaling pathway. METHODS SONFH model in rabbits was induced by injecting Escherichia coli endotoxin+methylprednisolone. The successfully modeled rabbits were randomly divided into Model group （normal saline）， low-dose PACs group （PACs-L group， 11 mg/kg）， high-dose PACs group （PACs-H group， 22 mg/kg）， high-dose PACs+ RIPK1 activator （rRIPK1） group （PACs-H+rRIPK1 group， 22 mg/kg PACs+4 μg/kg rRIPK1）， along with a control group （normal saline）， with 6 rabbits in each group. Each administration group was given relevant medicine once a day intragastrically/via injection， for 4 consecutive weeks. After the last administration， the levels of tumor necrosis factor-α （TNF-α） and interleukin-6 （IL-6） in rabbit serum were measured. The changes in the microstructure of rabbit femurs， including bone mineral density （BMD）， trabecular thickness （Tb.Th）， trabecular number （Tb.N）， and trabecular separation （Tb. Sp） were examined. The histopathological features of rabbit femoral tissues were observed， and the apoptotic status of cells within the rabbit femoral tissues was detected. The mRNA expressions of vascular endothelial growth factor （VEGF） and bone morphogenetic protein 2 （BMP2） in rabbit femoral tissues were determined. The expressions of RIPK1/RIPK3/MLKL signaling pathway-related proteins in femoral tissues were detected. RESULTS Compared with the Control group， serum contents of TNF-α and IL-6， Tb.Sp， empty bone cavity rate， cell apoptosis rate， phosphorylation levels of RIPK1， RIPK3 and MLKL in femoral tissue were significantly increased in the Model group （P＜0.05）. BMD， Tb.Th， Tb.N， as well as the mRNA expression of VEGF and BMP2， along with protein expression of caspase-8， in the femoral tissues were all decreased （P＜0.05）. The bone cells in the femoral tissue were unevenly distributed， and the trabeculae were arranged sparsely. Compared with the Model group， the aforementioned quantitative indicators （P＜0.05） and pathological changes in all dosage groups of PACs showed significant improvements. Compared with the PACs-H group， the aforementioned quantitative indicators （P＜0.05） and pathological changes in the PACs-H+rRIPK1 group showed significant reversal. CONCLUSIONS PACs can ameliorate SONFH in rabbits， and its mechanism of action may be related to the inhibition of the activation of the RIPK1/RIPK3/MLKL signaling pathway， suppression of apoptosis in femoral tissue cells， and promotion of angiogenesis.

Flood disasters frequently occur in schistosomiasis-endemic regions of China during the flood season, which causes a high risk of schistosomiasis transmission. Therefore, it is particularly crucial to control schistosomiasis transmission during the flood season. Based on field schistosomiasis control needs, this article proposes scientifical and operational countermeasures during three phases of pre-flood preparation, response to flood disasters, and post-flood management, and emphasizes multi-faceted interventions as responses to the risk of Oncomelania hupensis spread and schistosomiasis transmission caused by flood disasters, including information collection, risk assessment, material reserve, health education, Oncomelania hupensis control, cercariae elimination, personal protection, and preventive treatment, so as to provide insights into schistosomiasis prevention and control during the flood season.